The present disclosure relates to investigation of earth formations and, more particularly, to techniques for displaying sonic well logging information in a manner which provides for reliable quality-control (QC) indicators.
It is well known that mechanical disturbances can be used to establish acoustic waves in earth formations surrounding a borehole, and the properties of these waves can be measured to obtain important information about the formations through which the waves have propagated. Parameters of compressional, shear and Stoneley waves, such as their velocity (or its reciprocal, slowness) in the formation and in the borehole, can be indicators of formation characteristics that help in evaluation of the location and/or producibility of hydrocarbon resources. An example of some techniques which may be used for determining properties of earth formations using sonic well logging is described in U.S. Pat. No. 6,614,716 to Plona et at, herein incorporated by reference in its entirety for all purposes.
Sonic logging tools may be used to collect an array of waveforms from either monopole, dipole or quadrupole sources. Wireline logging tools typically use the monopole and dipole modes, while drilling sonic tools (LWD) use the monopole and quadrupole modes. Each of the different modes generates an array of waveforms which can be processed using a variety of techniques to obtain an estimate of formation slowness. One such technique is semblance processing, described, for example, in U.S. Pat. No. 4,594,691 to Kimball et al., herein incorporated by reference in its entirety for all purposes. In the semblance processing technique, data is gathered and processed from an array of received waveforms from a particular source (e.g., dipole source) at one particular depth. This is illustrated, for example, in FIG. 1A.
FIGS. 1A-B show a set of model calculations for acoustic wave propagation in a circular borehole with a centralized dipole source. FIG. 1A shows an array of 6 received waveforms from a dipole source at one particular depth. In these waveforms one observes two arrivals moving across the array. The first arrival in time is a dipole compressional signal 104, and the second, later in time signal, is the arrival of the dipole flexural signal 102. In conventional semblance processing, the semblance parameter as a function of wave slowness vs. time is calculated and displayed as shown, for example, in FIG. 1B. FIG. 1B illustrates a graphical representation of the Slowness-Time-Coherence (STC), or semblance, processing of the received waveforms of FIG. 1A. As shown in the example of FIG. 1B, a compressional semblance contour 114 is located near 125 μs/ft and a shear semblance contour 112 is located near 300 μs/ft. The local peak of the semblance contour is then plotted on a sonic log as the formation parameter (i.e., slowness) at each depth. A typical sonic log is shown, for example, in FIG. 2. FIG. 2 shows an example of a conventional slowness log, illustrating, for example, a compressional slowness curve 201 (green) from a monopole source, a fast shear slowness curve 203 (red) from a dipole source, a slow shear slowness curve 205 (blue) from a dipole source, and a monopole Stoneley slowness curve 207 (purple).
For dipole flexural data, it is well-known that the low frequency limit (e.g., zero frequency) of a dipole flexural curve asymptotes to the true formation shear speed. Thus, in conventional semblance processing, it is desirable that the peak semblance calculation at each depth correspond to the low frequency limit of the dispersion curve at that depth. In this regard, various techniques have conventionally been used to help ensure that the calculated peak semblance data correspond to the low frequency limits of their respective flexural dispersion curves. However, as described in greater detail below, there are currently no mechanisms available by which to adequately quality control the accuracy of such techniques.
For example, a current technique for quality control corresponds to projecting the semblance contours onto the slowness axis to derive a one dimensional set of numbers at each depth, and then use this data to generate an estimate of shear slowness of the flexural dispersion curves across multiple depths. Such a technique is illustrated, for example, in FIGS. 3A-E of the drawings.
FIG. 3A-E illustrate a conventional procedure for constructing a Slowness-Time-Coherence (i.e., semblance) projection log which may be used for quality control analysis of sonic logs. As shown in FIGS. 3A-B, the semblance contours 302, 304 are projected onto the slowness axis to derive a one dimensional set of numbers 310. The slowness projections at each depth are rotated (FIG. 3C) and compiled to generate a log 330 of slowness projection as a function of depth, as shown, for example, in FIG. 3D. Finally, as shown in FIG. 3E, the estimated shear slowness curve (dts) 336 is plotted on top of the log projection 330.
A significant problem with quality control display of FIG. 3E, however, is that there is no way of knowing from the displayed information if the estimated dts 336 actually corresponds to the low frequency limit of the dipole flexural dispersion curve at each depth. Since the estimated dts curve 336 may be generated using a variety of mathematical algorithms and/or computer data processing techniques, errors in the calculation of the estimated dts may result in a poor quality estimated dts curve which does not correspond to the low frequency limit of the dipole flexural. Thus it will be appreciated that there exists a need to provide improved quality-control (QC) indicators for sonic logging data.